Submitted by Clebson Anjos (clebson.leandro54@gmail.com) on 2016-02-11T20:45:07Z No. of bitstreams: 1 arquivototal.pdf: 2311643 bytes, checksum: 43ddbb48531f37b68376b2f7a5285c70 (MD5) / Made available in DSpace on 2016-02-11T20:45:07Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2311643 bytes, checksum: 43ddbb48531f37b68376b2f7a5285c70 (MD5) Previous issue date: 2014-07-31 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Social network analysis techniques can be used to extract knowledge from the network by analyzing the interactions between its members. In this work we intend to apply echniques of social network analysis on networks formed through scientific collaborations among researchers. Our objective with this study is to analyze if these collaboration connections may have any influence in the evaluation of scientific merit. We will focus our work on two specific scenarios. The first scenario targets the evaluation of individual merit for granting scholarships to researcher and is conducted by CNPQ, the Brazilian Research Council. The second scenario focus on the evaluation of graduate programs in the country and is conducted by CAPES, the governmental body entitled to evaluate and coordinate the graduate education program in Brazil. On both scenarios we will restrict our analysis to the Computer Science area. / Técnicas de análise de redes sociais podem ser utilizadas para extrair conhecimento da rede por meio da análise das interações entre seus membros. Neste trabalho pretendemos aplicar técnicas de análise de redes sociais a redes formadas pela colaborações científicas entres pesquisadores. Pretendemos com isso avaliar se as relações de colaboração entre pesquisadores possuem alguma influência na avaliação do mérito científico. Utilizaremos como estudos de caso o processo de concessão das chamadas bolsas de produtividade em pesquisa do CNPQ e a avaliação dos programas de pós-graduação pela CAPES, ambos focados na área de Ciência da Computação.

Submitted by BRUNO HENRIQUE ALVES null (bruninkmkt@hotmail.com) on 2018-02-08T02:55:23Z No. of bitstreams: 1 Versão final da tese digital-Bruno Henrique Alves.pdf: 2708337 bytes, checksum: ffa01244f503bfa9fd105ec7d823a7d7 (MD5) / Approved for entry into archive by Satie Tagara (satie@marilia.unesp.br) on 2018-02-08T13:17:16Z (GMT) No. of bitstreams: 1 alves_bh_dr_mar.pdf: 2708337 bytes, checksum: ffa01244f503bfa9fd105ec7d823a7d7 (MD5) / Made available in DSpace on 2018-02-08T13:17:16Z (GMT). No. of bitstreams: 1 alves_bh_dr_mar.pdf: 2708337 bytes, checksum: ffa01244f503bfa9fd105ec7d823a7d7 (MD5) Previous issue date: 2018-02-06 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / O Campo da Ciência da Informação (CI) é um espaço hierarquizado, relativamente autônomo e formado por relações objetivas que se dão em um contexto social pelos diferentes agentes e/ou instituições. Esta pesquisa objetivou compreender os mecanismos implícitos à geração e construção do conhecimento dos pesquisadores bolsistas de produtividade em pesquisa do CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) em CI e a posição social que ocupam no Campo em questão. De forma mais específica, pretendeu apresentar, de forma diacrônica, os pesquisadores bolsistas de produtividade em pesquisa do CNPq em CI; agrupar os diferentes artigos produzidos pelos pesquisadores bolsistas de produtividade em pesquisa do CNPq em CI, segundo os temas dos GTs (Grupos de Trabalho) da ANCIB (Associação Nacional de Pesquisa e Pós-Graduação em Ciência da Informação); identificar os pesquisadores bolsistas de produtividade em pesquisa do CNPq em CI, que publicam artigos indexados em bases de dados internacionais e destacar sua inserção no contexto internacional; compreender os mecanismos sociais construídos para organizar e que facilitam a estruturação das redes de colaboração científica dos pesquisadores bolsistas de produtividade em pesquisa do CNPq em CI; fundamentar a Análise de Redes Sociais (ARS) a partir da teoria do Campo e os conceitos de Capital Social, Capital Científico, propostos pela Sociologia de Pierre Bourdieu, objetivando identificar a posição de dominantes e dominados que os bolsistas de produtividade em pesquisa do CNPq ocupam na CI. Como procedimento de pesquisa, realizou-se um levantamento de todos os artigos publicados pelos 47 pesquisadores bolsistas de produtividade do CNPq em CI, no período de 2005-2009 (primeiro quinquênio) e 2010-2014 (segundo quinquênio) em um total de 914 artigos publicados em periódicos. Para a construção das redes de colaboração científica entre os pesquisadores, utilizou-se o Software Ucinet. A teoria do Campo Científico será utilizada também para complementar o procedimento de Análise de Redes Sociais, focando a identificação, caracterização e evolução das redes de colaboração científica (2005-2009 e 2010-2014). Ainda, serão relacionados com os conceitos propostos pela Sociologia de Pierre Bourdieu, tendo em vista identificar a posição de dominantes e dominados na estrutura social do Campo da CI. Os 47 pesquisadores bolsistas PQ em CI publicaram, no período de 2005 a 2009, um total de 317 artigos, e os 56 pesquisadores PQ em CI publicaram, no período 2010 a 2014, um total de 597 artigos. Os GTs mais contemplados, respectivamente, no período 2005 a 2009 e 2010 a 2014 são: GT02 "Organização e Representação do Conhecimento e GT 08, que se refere à "Informação e Tecnologia". As redes de colaboração científica mostram a interlocução brasileira no contexto internacional. Como conclusões, destaca-se que, de acordo com os fundamentos desta pesquisa e da Sociologia de Pierre Bourdieu, para ocupar uma posição de dominante, o pesquisador bolsista de produtividade em pesquisa do CNPq deve entender a lógica do jogo, pois o Campo possui eixos estruturantes a partir dois quais se identificam os principais jogadores que ocupam esse espaço social de concorrência científica. / The field of Information Science (IS) is a hierarchical space, relatively autonomous and formed by objective relations that take place in a social context among different agents and / or institutions. This research aimed to understand the implicit mechanisms for the generation and construction of the knowledge of the CNPq (National Council for Scientific and Technological Development) fellow researchers in IS and the social position they occupy in the field. More specifically, the research intended to present, diachronically, the IS CNPq fellow researchers; to group the different articles produced by the IS CNPq fellow researchers according to the themes by ANCIB (National Association of Research and Post-Graduation in Information Science) Working Groups; to identify IS CNPq fellows who publish articles indexed in international databases and to evaluate their insertion in the international context; to understand the social mechanisms built to organize and which facilitate the structuring of the scientific collaboration networks of IS CNPq fellow researchers; to base the Social Network Analysis (SNA) from the Field Theory and the concepts of Social Capital, Science Capital, proposed by the Sociology of Pierre Bourdieu, aiming to identify the dominant and dominated position that the CNPq fellow researchers occupy in IS. As a research procedure, a survey of all the articles published by the 47 CNPq fellow researchers in IS between 2005-2009 (first five years) and 2010-2014 (second five years) was carried out, totaling 914 articles published in journals. The software Ucinet was used for the construction of the scientific collaboration networks among researchers. The scientific Field Theory will also be used to complement the procedure of Social Network Analysis, focusing on the identification, characterization and evolution of scientific collaboration networks (2005-2009 and 2010-2014). In addition, they are related to the concepts proposed by the Sociology of Pierre Bourdieu in order to identify the position of dominant and dominated in the social structure of the field of IS. The 47 IS CNPq fellow researchers published a total of 317 articles in the period between 2005 and 2009, and the 56 IS CNPq fellow researchers published, in the period between 2010 and 2014, a total of 597 articles. The most contemplated WGs, respectively, in the period between 2005 and 2009, and between 2010 and 2014 are: WG 02 " Knowledge Organization and Representation” and WG 08 " Information and Technology. "Scientific collaboration networks show Brazilian interlocution in the international context. In conclusion, according to the foundations of this research and the Sociology of Pierre Bourdieu, in order to occupy a dominant position, the IS CNPq researcher must understand the logic of the practice, since the Field has structuring axes from which one can identify the main players that occupy this social space of scientific competition. / 140860/2014-2

O avanço da tecnologia nos últimos anos permitiu a criação de Sistemas de Informação com acesso a grandes bases de dados, abrindo diversas possibilidades de aplicações. Tem-se como exemplo a Internet, onde uma enorme quantidade de dados é gerada e publicada a todo momento por usuários ao redor do mundo. Com isso, aos poucos foi surgindo a necessidade de métodos para filtrar o conteúdo disponível de forma a permitir que um usuário pudesse focar apenas nos seus interesses. Nesse contexto surgiram os Sistemas de Recomendação e as Redes Sociais, onde, mais recentemente, surgiram trabalhos que apresentam abordagens para o uso de Sistemas de Recomendação no contexto acadêmico, de forma a aumentar a produtividade de grupos de pesquisa. Também têm sido bastante exploradas formas de se utilizar informações temporais em Sistemas de Recomendação de maneira a melhorar as recomendações feitas. O presente trabalho propõe uma abordagem de recomendação de colaborações acadêmicas utilizando a técnica de Análise de Séries Temporais, buscando melhorar os resultados obtidos por trabalhos anteriores. Foi realizado um experimento offline para avaliar o desempenho da abordagem proposta em relação às abordagens anteriores e um estudo de usuários para fazer uma análise mais profunda com feedback de usuários. Foram utilizadas métricas conhecidas das áreas de Recuperação de Informação e Sistemas de Recomendação, mas alguns resultados se mostraram inferiores em comparação com as abordagens existentes; outros, porém, foram similares. Também foram utilizadas algumas métricas de avaliação focadas em Sistemas de Recomendação, e os resultados obtidos foram similares em todas as abordagens testadas. / The advance of technology in recent years made possible the creation of Information Systems with access to large databases, opening many applications possibilities. There’s the Internet, for example, where a vast amount of data is generated and published all the time by users around the world. In this sense, the need for methods to filter the available content to enable users to focus only on their interests slowly emerged. In this context, Recommender Systems and Social Networks appeared, where, recently, works reporting approaches to provide recommendations in the academic context appeared, increasing the productivity of research groups. New ways to employ temporal information in Recommender Systems to make better recommendations are also being explored. The present work proposes an approach to academic collaborations recommendation using Time Series Analysis, aiming to improve results reported on previous and current works. An offline experiment was done to evaluate the proposed approach in comparison with other works and a user study was done to make a deeper analysis from user feedback. Known metrics from the Information Retrieval and Recommender Systems fields were used, and in some cases the results obtained were lower compared to the current methods but similar in others. Some evaluation metrics from Recommender Systems were also used, and the results were similar to all approaches.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Compreender a dinÃmica de produÃÃo e colaboraÃÃo em pesquisa pode revelar melhores estratÃgias para carreiras cientÃficas, instituiÃÃes acadÃmicas e agÃncias de fomento. Neste trabalho nÃs propomos o uso de uma grande e multidisciplinar base de currÃculos cientÃficos brasileira, a Plataforma Lattes, para o estudo de padrÃes em pesquisa cientÃfica e colaboraÃÃes. Esta base de dados inclui informaÃÃes detalhadas acerca de publicaÃÃes e pesquisadores. CurrÃculos individuais sÃo enviados pelos prÃprios pesquisadores de forma que a identificaÃÃo de coautoria nÃo à ambÃgua. Pesquisadores podem ser classificados por produÃÃo cientÃfica, localizaÃÃo geogrÃfica e Ãreas de pesquisa. Nossos resultados mostram que a rede de colaboraÃÃes cientÃficas tem crescido exponencialmente nas Ãltimas trÃs dÃcadas, com a distribuiÃÃo do nÃmero de colaboradores por pesquisador se aproximando de uma lei de potÃncia à medida que a rede evolui. AlÃm disso, ambas a distribuiÃÃo do nÃmero de colaboradores e a produÃÃo por pesquisador seguem o comportamento de leis de potÃncia, independentemente da regiÃo ou Ãreas, sugerindo que um mesmo mecanismo universal pode ser responsÃvel pelo crescimento da rede e pela produtividade dos pesquisadores. TambÃm mostramos que as redes de colaboraÃÃo investigadas apresentam um tÃpico comportamento assortativo, no qual pesquisadores de alto nÃvel (com muitos colaboradores) tendem a colaborador com outros semelhantes. Em seguida, mostramos que homens preferem colaborar com outros homens enquanto mulheres sÃo mais igualitÃrias ao estabelecer suas colaboraÃÃes. Isso à consistentemente observado em todas as Ãreas e à essencialmente independente do nÃmero de colaboraÃÃes do pesquisador. A Ãnica exceÃÃo sendo a Ãrea de Engenharia, na qual este viÃs à claramente menos pronunciado para pesquisadores com muitas colaboraÃÃes. TambÃm mostramos que o nÃmero de colaboraÃÃes segue o comportamento de leis de potÃncia, com um cutoff dependente do gÃnero. Isso se reflete no fato de que em mÃdia mulheres produzem menos artigos e tÃm menos colaboraÃÃes que homens. TambÃm mostramos que ambos os gÃneros exibem a mesma tendÃncia quanto a colaboraÃÃes interdisciplinares, exceto em CiÃncias Exatas e da Terra, nas quais mulheres tendo mais colaboradores sÃo mais propensas a pesquisas interdisciplinares. / Understanding the dynamics of research production and collaboration may reveal better strategies for scientific careers, academic institutions and funding agencies. Here we propose the use of a large and multidisciplinary database of scientific curricula in Brazil, namely, the Lattes Platform, to study patterns of scientific production and collaboration. Detailed information about publications and researchers is available in this database. Individual curricula are submitted by the researchers themselves so that co-authorship is unambiguous. Researchers can be evaluated by scientific productivity, geographical location and field of expertise. Our results show that the collaboration network is growing exponentially for the last three decades, with a distribution of number of collaborators per researcher that approaches a power-law as the network gets older. Moreover, both the distributions of number of collaborators and production per researcher obey power-law behaviors, regardless of the geographical location or field, suggesting that the same universal mechanism might be responsible for network growth and productivity. We also show that the collaboration network under investigation displays a typical assortative mixing behavior, where teeming researchers (i.e., with high degree) tend to collaborate with others alike. Moreover, we discover that on average men prefer collaborating with other men than with women, while women are more egalitarian. This is consistently observed over all fields and essentially independent on the number of collaborators of the researcher. The solely exception is for engineering, where clearly this gender bias is less pronounced, when the number of collaborators increases. We also find that the distribution of number of collaborators follows a power-law, with a cut-off that is gender dependent. This reflects the fact that on average men produce more papers andhave more collaborators than women. We also find that both genders display the same tendency towards interdisciplinary collaborations, except for Exact and Earth Sciences, where women having many collaborators are more open to interdisciplinary research.

A análise de redes sociais permite estudar a maneira como são estabelecidas as conexões entre indivíduos e como estas evoluem ao longo do tempo. A coautoria é uma das formas mais estudadas e bem documentadas de colaboração científica. Existem muitos aspectos de redes de colaboração científica, os quais podem ser rastreados de forma confiável através da análise de redes de colaboração usando métodos bibliométricos. Diversos esforços em diferentes áreas de pesquisa tentam analisar, entender, explicar e predizer o comportamento de sistemas modelados através de redes sociais. Nestes estudos, os indivíduos são modelados como vértices de um grafo, enquanto as relações entre eles são representadas por arestas. Atualmente, o estudo de redes de colaboração científica é importante e necessário para apoiar o planejamento estratégico, implementação e gestão dos programas de pesquisa científica. Neste trabalho, apresentamos um modelo de análise de redes científicas baseado em Grafos Relacionais com Atributos (ARG). O modelo proposto permite representar as redes de colaboração científica incluindo atributos individuais dos pesquisadores e atributos dos trabalhos colaborativos de pares de pesquisadores. Os dados correspondem às produções científicas de pesquisadores cadastrados na plataforma Lattes e extraídas automaticamente usando a ferramenta scriptLattes. Na primeira etapa, foi implementado o cálculo automatizado da taxa de internacionalização de cada pesquisador, a qual mostra a proporção entre o número de publicações internacionais e o número total de publicações. Esta medida junto com a produção científica individual discretizada em diversos grupos fazem parte das informações armazenadas nos vetores de atributos dos vértice dos ARGs. Por outro lado os vetores de atributos das arestas armazenam informações dos trabalhos colaborativos discretizados segundo a classificação da CAPES. Adicionalmente, neste trabalho foram exploradas duas aplicações relacionadas à (i) predição de trabalhos colaborativos futuros e à (ii) influência dos pesquisadores na rede de colaboração. O resultado da predição de vínculos foi usado para determinar a influência dos pesquisadores na redes de colaboração. A influência tem sido explorada com base na variação da predição de ligações com a presença ou a ausência do pesquisador na rede. Nossa proposta foi avaliada considerando diferentes testes sobre redes de coautoria científica de diversos grupos de pesquisadores. Os resultados obtidos são promissores para a análise de redes sociais em geral. / The social network analysis allows the study of how the relationships are established between individuals and how their are evolving with the time. The co-authorship is one of the most studied and documented scientific collaboration. There are some aspects which could be traced in a reliable way through the social network analysis using bibliometric methods. There are several proposals in different research areas trying to analyse, understand, explain and predict the behaviour of systems modeled as social networks. In this study, the individuals are modeled as vertices of a graph, while the relationships between them are represented by edges. Currently the study of scientific collaboration networks is important and necessary to support the strategic planning, implementation and management of scientific research programs. In this work, we present an scientific networks analysis model based on Attributed Relational Graphs (ARG). The proposed model allows to represent the scientific collaboration networks including individual attributes of researchers and attributes of the collaborative work of researchers pairs. The data correspond to the scientific production of researchers, registered in the Lattes Platform and automatically extracted using the tool scriptLattes \\citep{Mena-Chalco:2009}. In the first step, was implemented the automated computation of the internationalization rate for each researcher, that shows the ratio between the number of international publications and the total number of publications. This measure together with the individual scientific production discretized in diverse groups form part of the information stored in the vertices of the ARGs. On the other hand, the edges store information of collaborative work discretized according to the CAPES classification. Additionally, this work explores two related applications (i) prediction of future collaborative work and (ii) influence of researchers in collaboration network. The result of the link prediction was used to determine the influence of researchers in collaborative networks. The influence in collaboration network is computed based on the variation of the link prediction with the presence or absence of the researcher in the network. Our proposal was evaluated with different real scientific co-authorship networks and with different research groups. The results obtained look promising for analyzing social networks in general.

A análise de redes sociais permite estudar a maneira como são estabelecidas as conexões entre indivíduos e como estas evoluem ao longo do tempo. A coautoria é uma das formas mais estudadas e bem documentadas de colaboração científica. Existem muitos aspectos de redes de colaboração científica, os quais podem ser rastreados de forma confiável através da análise de redes de colaboração usando métodos bibliométricos. Diversos esforços em diferentes áreas de pesquisa tentam analisar, entender, explicar e predizer o comportamento de sistemas modelados através de redes sociais. Nestes estudos, os indivíduos são modelados como vértices de um grafo, enquanto as relações entre eles são representadas por arestas. Atualmente, o estudo de redes de colaboração científica é importante e necessário para apoiar o planejamento estratégico, implementação e gestão dos programas de pesquisa científica. Neste trabalho, apresentamos um modelo de análise de redes científicas baseado em Grafos Relacionais com Atributos (ARG). O modelo proposto permite representar as redes de colaboração científica incluindo atributos individuais dos pesquisadores e atributos dos trabalhos colaborativos de pares de pesquisadores. Os dados correspondem às produções científicas de pesquisadores cadastrados na plataforma Lattes e extraídas automaticamente usando a ferramenta scriptLattes. Na primeira etapa, foi implementado o cálculo automatizado da taxa de internacionalização de cada pesquisador, a qual mostra a proporção entre o número de publicações internacionais e o número total de publicações. Esta medida junto com a produção científica individual discretizada em diversos grupos fazem parte das informações armazenadas nos vetores de atributos dos vértice dos ARGs. Por outro lado os vetores de atributos das arestas armazenam informações dos trabalhos colaborativos discretizados segundo a classificação da CAPES. Adicionalmente, neste trabalho foram exploradas duas aplicações relacionadas à (i) predição de trabalhos colaborativos futuros e à (ii) influência dos pesquisadores na rede de colaboração. O resultado da predição de vínculos foi usado para determinar a influência dos pesquisadores na redes de colaboração. A influência tem sido explorada com base na variação da predição de ligações com a presença ou a ausência do pesquisador na rede. Nossa proposta foi avaliada considerando diferentes testes sobre redes de coautoria científica de diversos grupos de pesquisadores. Os resultados obtidos são promissores para a análise de redes sociais em geral. / The social network analysis allows the study of how the relationships are established between individuals and how their are evolving with the time. The co-authorship is one of the most studied and documented scientific collaboration. There are some aspects which could be traced in a reliable way through the social network analysis using bibliometric methods. There are several proposals in different research areas trying to analyse, understand, explain and predict the behaviour of systems modeled as social networks. In this study, the individuals are modeled as vertices of a graph, while the relationships between them are represented by edges. Currently the study of scientific collaboration networks is important and necessary to support the strategic planning, implementation and management of scientific research programs. In this work, we present an scientific networks analysis model based on Attributed Relational Graphs (ARG). The proposed model allows to represent the scientific collaboration networks including individual attributes of researchers and attributes of the collaborative work of researchers pairs. The data correspond to the scientific production of researchers, registered in the Lattes Platform and automatically extracted using the tool scriptLattes \\citep{Mena-Chalco:2009}. In the first step, was implemented the automated computation of the internationalization rate for each researcher, that shows the ratio between the number of international publications and the total number of publications. This measure together with the individual scientific production discretized in diverse groups form part of the information stored in the vertices of the ARGs. On the other hand, the edges store information of collaborative work discretized according to the CAPES classification. Additionally, this work explores two related applications (i) prediction of future collaborative work and (ii) influence of researchers in collaboration network. The result of the link prediction was used to determine the influence of researchers in collaborative networks. The influence in collaboration network is computed based on the variation of the link prediction with the presence or absence of the researcher in the network. Our proposal was evaluated with different real scientific co-authorship networks and with different research groups. The results obtained look promising for analyzing social networks in general.

In this introductory Chapter the rationale for this research is explained and an overview of the thesis is provided. This chapter serves as a concise introduction to the subject of the knowledge base and knowledge pipelines in a metropolis as Brussels, as well as providing an insight into the policy driven empirical research with additional focus on the appropriate spatial level of analysis to highlight the spatial inequality of innovation. The objectives of the thesis are reviewed by giving an overview of the research questions and the main hypotheses related to them. The theoretical background used in this thesis is briefly outlined. The structure of the thesis can be summarised as follows. The second chapter provides basic information about data on patents and scientific publications, the construction of indicators based on patents and scientific publications, as well as guidelines for the compilation and interpretation of patent and scientific publication indicators. The third chapter focuses on the determinants of the efficiency levels across regions in Belgium at different spatial levels. The fourth chapter builds on the research made in the previous chapters and focuses on the analysis of the impact of patent collaboration networks on the output growth of R&D active companies in Belgium. The fifth chapter analyses the impact of different collaboration ties on the productivity of innovative companies in Belgium, measured in several ways through the innovation survey and in terms of patents. The conclusion reported in the last chapter summarises the main findings and highlight possible suggestions for future research. / Benchmarking exercises are increasingly used as an assessment instrument to guide policy-makers. They contribute to policy-making in three broad ways: delineating and monitoring development and progress; facilitating the exchange and gathering of knowledge on practices and policies; and promoting the image and attractiveness of economies. This research complements existing information about the Brussels Regional Innovation System (BRIS) with additional data that is less frequently available through current channels or difficult to make public due to the number of data manipulations. This research illustrates the Brussels innovation system by focusing on various aspects related to intra- and interregional connections. The dataset is based on scientific publications and patents over the period 1993-2013 containing at least one author with an affiliation or one inventor located in the Brussels-Capital Region, Vienna and Berlin. Patents and scientific publications provide a clear picture of the nature of technological change and innovation. Moreover, these sources give some further indication of R&D activities in the field and the position and specialisation of countries. The main benefit of such indicators is the unique empirical characterization they provide of the way actors interact as a collective system of knowledge production and diffusion (OECD, 1996). The main objective of this work is to compare Brussels with Belgian regions, city agglomerations and districts, as well as with capital cities of metropolitan regions (Vienna and Berlin) in terms of patenting and producing scientific publications, in order to map and understand how knowledge exchange takes place when Brussels actors are involved and which partners, locations, scientific fields and technological sectors are preferred. The main focus is on providing basic information about patent and scientific publication data, the construction of indicators based on patents and scientific publications, as well as guidelines for the compilation and interpretation of patent and scientific publication indicators. / The topic of the spatial pattern in R&D activities was investigated by several scholars. It is worthwhile to explore the dynamism and change of R&D activities’ spatial spread as R&D activities are very much a dynamic phenomenon and the consequences in terms of past growth of these activities have painted the current relative position of the regions. Analysing the determinants of the efficiency levels across Belgian regions at different spatial levels (3 regions, 10 provinces, 43 districts, and city agglomerations), we derive a regression based on the measurement of regional output growth by estimating an extended Cobb-Douglas production function based on a representative sample of Belgian R&D active firms over the period 2000-2013. We investigate the role played by knowledge (private and public R&D stocks) on the output growth by applying spatial econometric methods that account for both heteroscedasticity and spatial autocorrelation. The chapter focuses on the comparison of obtained results with previous studies based on Belgium. It turns out that a large part of output growth differences across the Belgian regions are explained by disparities in the endowments of these determinants. / Although the literature on the relations between patents and output growth of R&D active companies has been widely investigated, there has been little research with respect to the impact of patent collaboration networks on the output growth of R&D active companies. Integrating theoretical developments from the literature, we propose and test a conceptual framework that allows us to explain to what extent patent collaboration networks affect output growth. Testing the framework by using a constructed company-level dataset for Belgium, the empirical analysis reveals that output growth is significantly influenced by patenting activities and by collaborative relations with respect to patents. The chapter focuses on two distinct spatial levels. First, the spatial reach of the patent collaboration network is considered. The findings show that output growth is higher when collaborative relations are internationally oriented. Second, the regional location of the company shows differences in patenting activity, patent collaboration, and the spatial reach of the patent collaboration network. / Inter-organisational relations are a crucial aspect of knowledge flows, which are at the same time an important engine for innovation. Collaboration has become an ever more important feature of entrepreneurial strategy to innovate. Network ties facilitate companies’ innovative capabilities by acting as key sources for innovations, helping to access the resources and boosting knowledge transfer. This chapter analyses the impact of different collaboration ties on the productivity of innovative companies in Belgium, measured in several ways through the innovation survey (Community Innovation Survey) and in terms of patents (Patstat). Patent statistics are used as an objective measure for innovation. Unlike patent data, innovation surveys measure innovation activities carried out in companies. This chapter is primarily concerned with the following research question: do collaboration networks, as measured by innovation surveys (CIS database) and by invention applications (Patstat database), impact productivity growth in the same way? Further, this chapter focuses on an alternative spatial approach in order to look into the role played by proximate and distant inter-organisational networks among organisations. The findings show that the collaboration ties between companies are contributing the most to productivity growth followed by collaboration ties involving universities and government, public or private research institutes. Second, the spatial reach of the inter-organisational networks shows divergent impact on productivity performance of innovating companies. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

This thesis aims to contribute to a fundamental objective of Network Economics: to provide based incentives explanations of real social network topologies. By using game theoretical tools, the three papers of this thesis analyze how real social networks can arise from the strategic interaction of self-interested individuals.In the first paper, we discuss the influence of imperfect information on the process of social network formation and, specifically, on the possibilities of observing racially segregated societies when agents' preferences are not racially biased. The second work attempts to complete the Network Economics' explanation of the puzzle regarding how agents can benefit from structural holes over a long time period. The third paper presents a model that focuses on the mechanisms underlying the formation of scientific collaboration networks. We show how researchers' heterogeneity and limited processing capability explain the basic characteristics of these networks. / Aquesta tesi aspira a contribuir a un objectiu fonamental de l'Economia de Xarxes: oferir explicacions basades en els incentius de les topologies que adopten les xarxes socials. Usant les eines de la Teoria de Jocs, els tres articles de la tesi analitzen com les xarxes socials que observem a la realitat poden esser fruit de la interacció entre individus que responen als seus propis interessos.En primer lloc, estudiem la influència de la informació imperfecte en la formació de xarxes socials i, específicament, en les possibilitats de tenir societats racialment segregades quan les preferències dels agents no estan racialment esbiaixades. El segon treball, intenta completar l'explicació que l'Economia de Xarxes dóna a l'interrogant referent als forats estructurals i a la gent que s'en beneficia de manera continuada. El darrer capítol, se centra en els mecanismes que expliquen la formació de xarxes de col·laboració científica. Es mostra com l'heterogeneïtat i la limitada capacitat de processament dels investigadors expliquen les caractarístiques bàsiques d'aquestes xarxes.